Freitag Gudrun
Institut fur Mathematische Stochastik, Georg-August-Universität Göttingen, Maschmühlenweg 8-10, 37073 Göttingen, Germany.
Biom J. 2005 Feb;47(1):88-98; discussion 99-107. doi: 10.1002/bimj.200410083.
In this paper we present the existing approaches to the problem of showing noninferiority with randomly right censored data. The main focus is on the choice of the discrepancy measure which is used to define the deviation from the classical null hypothesis, i.e. the noninferiority margin. Most methods are based on certain parametric or semiparametric assumptions. In contrast, a new, completely nonparametric approach is suggested and discussed.
在本文中，我们介绍了针对随机右删失数据的非劣效性检验问题的现有方法。主要关注点在于差异度量的选择，该差异度量用于定义与经典原假设（即非劣效性界值）的偏差。大多数方法基于某些参数或半参数假设。相比之下，本文提出并讨论了一种全新的完全非参数方法。
